Operate or tend heating equipment other than basic metal, plastic, or food processing equipment. Includes activities, such as annealing glass, drying lumber, curing rubber, removing moisture from materials, or boiling soap.
U.S. Workers
16,160
Median Salary
$47,010
10-Year Growth
+3.0%
Annual Openings
1,900
Typical entry: High school diploma or equivalent
18 of 18 tasks have some AI capability
Exposure Trend
This score reflects estimated AI technical capability for tasks in this occupation. It does not predict employment changes, and it does not account for company-specific constraints, regulation, or adoption barriers.
Monitor equipment operation, gauges, and panel lights to detect deviations from standards.
AI: Fully automatable - Sensor networks, SCADA, and AI anomaly-detection systems already monitor gauges and panel indicators and can detect deviations reliably.
Press and adjust controls to activate, set, and regulate equipment according to specifications.
AI: Fully automatable - Pressing and adjusting controls to activate and regulate equipment is routinely automated via PLCs and closed-loop control systems that meet specifications.
Record gauge readings, test results, and shift production in log books.
AI: Fully automatable - Recording gauge readings, test results, and production logs is commonly automated by instrument data capture and MES/SCADA integrations.
Read and interpret work orders and instructions to determine work assignments, process specifications, and production schedules.
AI: Fully automatable - Reading and interpreting digital work orders and producing assignments/schedules is well within existing MES and AI document-parsing plus planning systems.
Calculate amounts of materials to be loaded into furnaces, adjusting amounts as necessary for specific conditions.
AI: Fully automatable - Calculations and dynamic load adjustments can be fully automated using sensors, process control systems, and model-based or ML controllers integrated with plant instrumentation.
Transport materials and products to and from work areas, manually or using carts, handtrucks, or hoists.
AI: Fully automatable - Autonomous mobile robots, conveyors, and automated material-handling systems already perform the majority of intra-facility transport tasks in many facilities.
Weigh or measure specified amounts of ingredients or materials for processing, using devices such as scales and calipers.
AI: Fully automatable - Weighing and dimensional measurement are routine, highly automatable tasks using scales, vision systems, and automated fixtures with high reliability today.
Confer with supervisors or other equipment operators to report equipment malfunctions or to resolve production problems.
AI: Partial - AI can generate alerts and summaries, but human-to-human coordination, judgement, and negotiation to resolve production problems remain largely necessary.
Stop equipment and clear blockages or jams, using fingers, wire, or hand tools.
AI: Partial - Stopping equipment can be automated, but safely clearing blockages/jams frequently requires human dexterity, situational assessment, and manual tool use in unpredictable conditions.
Load equipment receptacles or conveyors with material to be processed, by hand or using hoists.
AI: Partial - Robotic loaders and automated hoists can handle repetitive loading in structured plants, but manual, variable, or cramped operations still require human work and supervision in 2025.
Examine or test samples of processed substances, or collect samples for laboratory testing, to ensure conformance to specifications.
AI: Partial - Laboratory testing and many inspections are highly automatable, but physical sample collection and nuanced quality judgments often still need human intervention.
Remove products from equipment, manually or using hoists, and prepare them for storage, shipment, or additional processing.
AI: Partial - Automated removal and material handling systems exist for standardized products, but varied shapes, delicate handling, and final preparation for shipment often still need human intervention or oversight.
Melt or refine metal before casting, calculating required temperatures, and observe metal color, adjusting controls as necessary to maintain required temperatures.
AI: Partial - Temperature control and visual monitoring can be automated, but complex metallurgical refinements and on-the-fly expert judgments about material behavior still commonly require skilled human operators.
Direct crane operators and crew members to load vessels with materials to be processed.
AI: Partial - AI can generate optimal lift plans and even autonomously control cranes in constrained settings, but directing mixed human crews and handling complex coordination and safety judgments remains partially manual.
Feed fuel, such as coal and coke, into fireboxes or onto conveyors, and remove ashes from furnaces, using shovels and buckets.
AI: Partial - Many plants use automated fuel feeding and ash handling, yet manual shoveling and ad hoc ash removal in legacy or variable operations still require human labor and adaptability.
Replace worn or defective equipment parts, using hand tools.
AI: Partial - Robotic manipulators can perform some parts replacement, but the dexterity, troubleshooting, and variability of field maintenance make full automation uncommon in 2025.
Clean, lubricate, and adjust equipment, using scrapers, solvents, air hoses, oil, and hand tools.
AI: Partial - Routine lubrication and some cleaning can be automated or scheduled, but detailed cleaning, adjustments, and solvent handling typically still need human judgment and dexterity.
Sprinkle chemicals on the surface of molten metal to bring impurities to surface and remove impurities, using strainers.
AI: Partial - Chemical dosing and slag-management systems can automate parts of impurity removal, but the precise timing, manual straining, and safety-sensitive interventions are often still performed or supervised by humans.